Machine translation systems are used to translate text from one language to another. These systems may use statistical models for guidance in translation by parsing the text into segments and then applying statistical models to arrive at a resulting translation. Models are most often learned by obtaining bilingual text corpora where the translations are known. The translations appear in parallel throughout several pages. The machine translation system will learn linguistic rules based on the parallel pages of text and apply the rules to new text. As a result, the more data (i.e., bilingual text) the machine translation system has been provided, the better the machine translation system functions. Currently, a large amount of textual data is overlooked by machine translation systems because it appears on multilingual pages instead of parallel pages.